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, including machine learning, computer vision, adaptive data modelling, and computational imaging. The objective is to develop state-of-the-art machine learning algorithms for solving ill-posed inverse problems
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publication record. Outstanding data analytics, mathematical, and computer modelling skills. Excellent interpersonal communication and oral presentation skills in English Self-driven and strong team spirit Open
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(or equivalent) in Computer Science, Machine Learning, Mathematics, or a related technical field. For Postdoctoral Fellows: A completed PhD in one of the fields mentioned above and a strong publication record
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collaborative mindset and excellent communication skills in English. Significant Advantage: Previous experience with adversarial machine learning, offensive security, or publications in top-tier conferences (e.g
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. Given their importance, continuous monitoring and fault diagnostics are crucial—especially as machine learning algorithms play an increasingly prominent role in predictive maintenance and reliability
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datasets. Experience in adapting and applying machine learning models to clinical data. Strong ability to communicate scientific work both internally within the research environment and externally to a
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, train, and validate advanced computational models and machine learning algorithms tailored to complex datasets. Collaborate with multidisciplinary teams including biologists, engineers, and clinicians
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in the western US. We lack timely forecasts of direction and rate of disease spread during an outbreak event. Modeling approaches will feature process-based machine learning in high-performance
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well as in a collaborative, team-oriented environment. Preferred Qualifications: Prior experience working with mouse models of cancer is strongly preferred; candidates without prior experience will be
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experience Evidence of experience with public-patient involvement and stakeholder engagement Track record in scientific publication and dissemination Experience with Machine Learning Algorithms and Artificial